The recent explosive growth of information storage and retrieval creates challenges for extracting meaningful information from large datasets of often seemingly unrelated information. Early methods of representing the information include scatter plots, bar graphs, pie charts, colored maps, tree structures and the like. For example, Microsoft® Excel™ enables viewing a data set as a table or as a chart, Spotfire and eBiz as interactively adjustable 2D and 3D scatter plots or in a parallel coordinate system; Inxight Eureka displays them in a table where numbers are replaced by small bars of length proportional to the value held in the cell. These products, as well as known research prototypes, such as Treemaps, The Influence Explorer or the Prosection Matrix are directed to a limited number of visualization types that are mapped from a data table to a set of graphic attributes. While those products allow customization, such as choosing the scale factors on a scatter plot, choosing the ordering of the columns, or choosing which values of the data are to be mapped onto the axes, none allows interactive browsing of the available space of the visualizations by adjusting a limited number of parameters.
It would therefore be desirable to provide an interactive editor that produces a class of visualizations that can be rendered in real time and thereby remain efficient even for large datasets.
It would further be desirable to provide a simple, but highly flexible user interface for accessing the available visualization created in this way.